The present disclosure is related generally to the field of orthodontics. More particularly, the present disclosure is related to a dental model system which can associate an abnormal tooth with a model tooth shape and map predefined dental references from the model shape onto the abnormal tooth to aid in accurately characterizing the tooth's positioning and/or movement.
Dental references provide feedback for dental measurements. For example, dental reference points can be used to characterize a tooth's movement, such as tipping and/or translation. Dental reference axes can be used to distinguish different directions of tooth positioning and/or movement.
Placement and/or identification of reference points can be done manually by a treatment professional or automatically through use of a computing device and executable instructions to make such identification and/or direct one or more devices to accomplish such placement. For example, the treatment professional can use a computing interface device to identify points on an image of a tooth displayed on a graphical user interface.
The treatment professional can also identify reference axes of the tooth in a similar fashion. However, manual selection of reference points and axes can yield inaccurate and inconsistent results.
As discussed above, automation of reference point selection can be performed with the assistance of a computing device. Algorithms in computing device-aided recognition of surface features can improve accuracy in some instances. For example, the maximum height of a crown can be detected by an algorithm that determines the location of cusp tips and this may improve the accuracy of reference point selection.
However, such automated systems are based on the assumption that the dental anatomy is normal. That is, the assumption that a tooth is fully intact and fully erupted.
Such automated systems rely on a set of dental features to identify reference points and axes. If a tooth is broken or partially erupted, an automated system may rely on incorrect landmarks to derive the reference points and axes.
In such situations, the automated system can incorrectly identify reference points and axes. This may result in impractical or incorrect treatment options.